#128 Building a Winning Data Team in Football, with Matt Penn
Learning Bayesian Statistics
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Takeaways:
- Matt emphasizes the importance of Bayesian statistics in scenarios with limited data.
- Communicating insights to coaches is a crucial skill for data analysts.
- Building a data team requires understanding the needs of the coaching staff.
- Player recruitment is a significant focus in football analytics.
- The integration of data science in sports is still evolving.
- Effective data modeling must consider the practical application in games.
- Collaboration between data analysts and coaches enhances decision-making.
- Having a robust data infrastructure is essential for efficient analysis.
- The landscape of sports analytics is becoming increasingly competitive.
- Player recruitment involves analyzing various data models.
- Biases in traditional football statistics can skew player evaluations.
- Statistical techniques should leverage the structure of football data.
- Tracking data opens new avenues for understanding player movements.
- The role of data analysis in football will continue to grow.
- Aspiring analysts should focus on curiosity and practical experience.
Chapters:
00:00 Introduction to Football Analytics and Matt's Journey
04:54 The Role of Bayesian Methods in Football
10:20 Challenges in Communicating Data Insights
17:03 Building Relationships with Coaches
22:09 The Structure of the Data Team at Como
26:18 Focus on Player Recruitment and Transfer Strategies
28:48 January Transfer Window Insights
30:54 Biases in Football Data Analysis
34:11 Comparative Analysis of Men's and Women's Football
36:55 Statistical Techniques in Football Analysis
42:48 The Impact of Tracking Data on Football Analysis
45:49 The Future of Data-Driven Football Strategies
47:27 Advice for Aspiring Football Analysts
51:29 Future Projects in Football Analytics
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau, Luis Fonseca, Dante Gates, Matt Niccolls, Maksim Kuznecov, Michael Thomas, Luke Gorrie, Cory Kiser, Julio, Edvin Saveljev, Frederick Ayala, Jeffrey Powell, Gal Kampel, Adan Romero, Will Geary, Blake Walters, Jonathan Morgan, Francesco Madrisotti, Ivy Huang, Gary Clarke, Robert Flannery, Rasmus Hindström, Stefan, Corey Abshire, Mike Loncaric, David McCormick, Ronald Legere, Sergio Dolia, Michael Cao, Yiğit Aşık and Suyog Chandramouli.
Links from the show:
- Matt on Linkedin: https://www.linkedin.com/in/matthew-penn-732551232/
- Matt on Google Scholar: https://scholar.google.com/citations?user=oY7jC7UAAAAJ&hl=en
- LBS #117, Unveiling the Power of Bayesian Experimental Design, with Desi Ivanova: https://learnbayesstats.com/episode/117-unveiling-power-bayesian-experimental-design-desi-ivanova/
Transcript
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